Going 'Viral' on Social Media: a Study of Popular Videos on Facebook

Going ‘Viral’ on Social Media: A Study of Popular Videos on Facebook

Prof. Archana R Singh Ishrat Singh Punjab University, India Abstract This study identifies ‘viral’ videos shared on official Facebook pages of three top leaders of Punjab, the state that is set to go for assembly elections in early 2017.Once the videos are identified, they will be analysed for various elements in the content. This study uses multi stage sampling process. In the first stage, the three top politicians belonging to three major parties are identified. The official Facebook pages of the selected political leaders are chosen as the universe of the study. The results of this study show that internet is not as effective a medium to reach the masses as far as the popular perception go because having large number of ‘views’ or ‘likes’ does not translate into a simple gesture such as ‘share’ in order for a video message to go viral. Keywords: viral, social media, political sphere,video

Introduction With the world increasingly going digital and political campaigns being driven online, one finds every political party trying hard to join the bandwagon and register an online presence. We have witnessed the phenomenon in the 2014 General Elections in India and are also witnessing it in the Presidential Race in the USA. The phenomenon is true not just for national level election campaigns but is evident in the assembly elections as well. This paper casts a look at the Punjab Assembly election scenario as the race to go ‘viral’ is on. In the politically- charged atmosphere of Punjab, social media is flooded with memes, trolls, videos, tweets, posts, all aiming to go ‘viral’. Be it Twitter, Facebook or YouTube, ‘trending’ and ‘viral’ content keeps ‘breaking’ the internet every day. This study compares the videos of three top political leaders of Punjab uploaded on their official Facebook pages to identify the viral ones. Just like the spread of an epidemic, from one living being to another in a very short time whose spread is uncontrolled, ‘viral’ content on the internet does the same. Initially called ‘e- worm’ or ‘electronic- word of mouth’ which means spreading by sharing from one person to the other, the concept has entered marketing, entertainment and even political campaigns. It’s not one of those concepts that lack credibility or affect only a section of people. ‘Viral’ and ‘trending’ are sections included in most websites today even if they are conglomerated with traditional media. The Indian Express has a ‘viral’ section in its e-edition which showcases viral videos and posts trending nationally and globally. The phenomena has also triggered credibility issues as many unconfirmed rumors go viral before the facts are out and this may prove disastrous to a person or organization. The website of ABP news has a section called ‘Vir a l Sach’ which means ‘viral truth’. These are unconfirmed reports which went viral on the internet. This study identifies ‘viral’ videos shared on official Facebook pages of three top leaders of Punjab, the state that is set to go into assembly elections in the early 2017. Once the videos are identified, they will be analysed for various elements in the content.

Figure 1: Viral or trending videos on www.indianexpress.com 7

Figure 2: Viral Sach on ABP News

Review of Literature In this review, which has been arranged in a thematic chronological manner, the researchers have tried to cast a look at the previous studies in the various areas of communication studies. The purpose of the review is to identify the aspects that make a video go viral so that they can be studied in the context of the social media campaigning of the political parties in Punjab. Advertising: In one of the earliest studies conducted on viral messages, Lance Porter and Guy J. Golan in their 2006 journal article ‘From subservient chickens to brawny men: a comparison of viral advertising to television advertising’ have referred to electronic word of mouth as viral advertising, thereby coining the term. “Significantly more than traditional advertising, viral advertising relies on provocative content to motivate unpaid peer- to-peer communication of persuasive messages from identified sponsors” (Golan, Lance Porter and Guy J., 2006). This study proves that such viral content uses raw emotions and “devices of sex, nudity, and violence are what motivate consumers to pass along content online.” This study also found that bigger companies like the Fortune 500 ones are less likely to use this kind of advertising but the number is increasing owing to the success of this method. The study finds that humour is the most common appeal followed by sex and nudity especially because these ads are unregulated unlike television. This exploratory study analyzed a total of 501 advertisements through content analysis method. In a similar study conducted in 2011 by Blaise Jenkins, th e c omparative content analysis method was followed. His paper was titled ‘Consumer Sharing of Viral Video Advertisements: A Look into Message and Creative Strategy Typologies and Emotional Content’. The paper studied some viral advertisements and identified their features. A key finding was that none of the advertisements used a comparative strategy, comparing t h e m to other brands. However, every advertisement used unique selling proposition and brand image strategy. The main finding that transforms online video advertising is the use of brand image strategy: focusing primarily on the brand (image) itself, not the users (Jenkins, 2011). It is an exploratory study that examines 30 viral online ads. In the same year Petya Eckler and Paul Bolls in their study titled, ‘Spreading the virus: emotional tone of viral advertising and its effect on forwarding intentions and attitudes’ extend knowledge by exploring how the emotional tone (pleasant, unpleasant, coactive) of viral video ads affects attitude toward the ad, attitude toward the brand, and forwarding intentions. Results indicate that pleasant 8

Amity Journal of Media & Communication Studies (ISSN 2231 – 1033) Copyright 2016 by ASCO 2016, Vol. 6, No. 2 Amity University Rajasthan emotional tone elicits the strongest attitude toward the advertisement, attitude toward the brand, and intention to forward. The effects were weaker for coactive tone and weakest for negative emotional tone. These results challenge the common approach of shocking or scaring online users to motivate them to forward a viral video. The results indicate that in the context of product viral video advertising, emotional tone has a simple linear relationship with both attitudes and intentions. It used survey method in which participants watched viral ads and then filled a questionnaire (Bolls, 2011). Research questions were addressed with an experiment that incorporated a 3 (emotional tone) × 4 (ad) within-subjects repeated measures design. All participants viewed 12 video ads, or 4 ads in each level of emotional tone (pleasant, unpleasant, and coactive). There is always a mystery surrounding the reasons of the viral phenomenon. Christian Schulze, Lisa Schöler, & Bernd Skiera demystified the reasons behind this with their study titled, ‘Not All Fun and Games: Viral Marketing for Utilitarian Products’. This study aims to answer questions that link product characteristics and contexts to viral marketing success: Should primarily utilitarian products rely on the same sharing mechanisms for their viral marketing campaigns as less utilitarian products? If not, why is this the case, and how should viral marketing for primarily utilitarian products differ? Unsolicited and incentivized broadcast messages from friends are the least effective sharing mechanisms for primarily utilitarian products. Consumers generally do not visit Facebook to learn about utilitarian products, so they process viral marketing messages about such products differently than, say, messages about games. Stark differences were found in the effectiveness of sharing mechanism characteristics for different types of products. A survey of 751 apps by noting the downloads and sharing on Facebook was mathematically coded and success was proposed through models (Christian Schulze, Lisa Schöler, & Bernd Skiera, 2014). Proposed conceptual model was tested with a large-scale empirical study based on 751 Facebook apps; collected information about the number and characteristics of the sharing mechanisms employed in each app. A team of coders, thoroughly trained by the authors, evaluated the app characteristics. Videos: On closer observation of the phenomenon, one notices that videos have a greater tendency to go viral. Kevin Wallsten in his 2009 paper ‘Yes We Can’: How Online Viewership, Blog Discussion, Campaign Statements and Mainstream Media Coverage Produced a Viral Video Phenomenon’ talks about how bloggers seem to occupy a unique and influential position in determining the extent to which online videos impact election campaigns (Wallsten, 2009). Results suggest that the discussions that take place on a blog and not the size of the audience are responsible in driving users towards a video and also getting media attention, thus making an election campaign successful. The research proves that interest of the bloggers in the video was the single largest reason for it going viral. This study includes only one political video, thus the results may or may not be true for only this video. Methodology used was that of detailed analysis of the video over time, blogs that were written about it and the print media attention it got. In the journal article, ‘Going Viral – The Dynamics of Attention’ of 2009 by Bob Boynton, ‘going viral’ has been interpreted in three ways. One is the high number of views for a video but it is a vague concept as there is no clarity as to how many views mean “viral”. The second way is the relation with the biological concept of the spreading of an epidemic. For something to go viral, a few users adopt it and spread it to others. “The structure of spreading the word is: 1) making it your own by adding a copy to your own blog or website, which has been made easier in the last year as embedding has become popular, 2) blogging, i.e., writing publicly about the video and ordinarily including a URL for the video, and 3) private communication that is also made easier by web connections” (Boynton, 2009). The third way is a functional form that says that if a video has less infected people at the start and end of its popularity, then it should form a sigmoid graph which was not true for the samples studied. He thus concludes that only the number of views for a video does not mean that it is viral. The study analysed the content and statistics related to all the campaign videos of presidential candidates and results showed that no video of 9

Amity Journal of Media & Communication Studies (ISSN 2231 – 1033) Copyright 2016 by ASCO 2016, Vol. 6, No. 2 Amity University Rajasthan the 2008 US presidential election campaign went viral. Similarly in a study by Tyler West, Going Viral: Factors That Lead Videos to Become Internet Phenomena’ (2011), 20 viral videos as listed by Times magazine are monitored to bring out the common elements which are responsible for a YouTube video going viral. “Understanding the prevalent elements within viral videos will allow for the prediction of which videos will become popular. This information will be useful for viral marketing campaigns” (West, 2011). Title length, run-time, element of laughter, surprise and irony, presence of minority and musical elements, youth and talent are some of the elements, which can be altered to make videos viral (revealed by results). The author examined the top 20 viral videos as determined by Time Magazine. Each video’s content was recorded for analysis of its main features. Predicting and controlling the virus: It is a general belief that virality can neither be predicted nor be controlled. Mauro Bampo, Michael T. Ewing, Dineli R. Mather, David Stewart and Mark Wallace in their 2008 journal article ‘The Effects of the Social Structure of Digital Networks on Viral Marketing Performance’, disprove the conventional belief that spread of viral messages are random and unmanageable (Mauro Bampo, 2008). It provides models for advertisers that can be helpful in controlling external as well as internal factors responsible for virality. The proposed models can be used to measure the impact of the viral campaign. Findings confirm that the social structure of digital networks play a critical role in the spread of a viral message. Analyses of viral marketing campaign and stimulation experiments were a part of the methodology. ‘A Viral Branching Model for Predicting the Spread of Electronic Word of Mouth’ ,a 2010 paper ,discusses the lack of models to help marketers to predict how many customers a viral marketing campaign will reach and how marketers can influence this process through marketing activities. This paper develops such a model using the theory of branching processes and empirical studies of real viral campaigns (Ralf van der Lans, Gerrit van Bruggen, Jehoshua Eliashberg and Berend Wierenga, 2010). The results show that the model quickly predicts the actual reach of the campaign. The model is applied to only one viral marketing campaign where it is successful but the same is a limitation of this study. Motivation and emotion: What emotions should an advertisement or video have so as to go viral? What factors can motivate users to share content enough to make it viral? A study in 2010, ‘A multi-stage model of word-of-mouth influence through viral marketing’, a model is developed to help identify the role word-of-m o uth plays during each stage of a viral marketing recipients' decision-making process, including the conditions that moderate such influence. It then presents an innovative methodology for collecting data unobtrusively and in real time. It empirically tests the model and methodology via a field study, where reactions of 1100 individuals were observed after they received an unsolicited e-mail from one of their acquaintances, inviting them to take a survey and in turn spread the word about it. It was found that characteristics of the social tie influenced recipients' behaviours but had different effects at different stages: tie strength facilitated awareness, perceptual affinity triggered recipients' interest, and demographic similarity had a negative influence on each stage of the decision-making process. It is an Internet-based field study using Stanley Milgram's ‘small world methodology’ (Arnaud De Bruyn, Gary L. Lilien, 2008). it was found while close relationships can be effective in capturing recipients' attention and creating awareness (e.g., to drive traffic to a website), they had no influence at later stages. ‘Viral marketing: Motivations to forward online content’ by Jason Y.C. Ho and Melanie Dempsey in 2010 identifies four potential motivations for sharing: (1) the need to be part of a group, (2) the need to be individualistic, (3) the need to be altruistic, and (4) the need for personal growth. “Using a survey of young adults, we examine the relationship between these motivations and the frequency of passing along online content. Results show that Internet users, who are more individualistic and/or more altruistic, tend to forward more online content than others.” (Jason Y.C. Ho, 2010) First, of the two motivations underlying the concept of inclusion, only individuation was positively related to the forwarding of online content. A survey was conducted for this study. Data were collected by sending 586 participants a link to an online survey which took approximately 30 min to 10

Amity Journal of Media & Communication Studies (ISSN 2231 – 1033) Copyright 2016 by ASCO 2016, Vol. 6, No. 2 Amity University Rajasthan complete. Similarly, ‘What Makes online Content Viral?’ was a question asked in a paper by the same name in 2011 by Jonah Berger and Katherine L. Milkman which takes a psychological approach to understanding diffusion. Using a unique data set of all the New York Times articles published over a three-month period, the authors examine how emotion shapes virality. The results indicate that positive content is more viral than negative content, but the relationship between emotion and social transmission is more complex than valence alone. Virality is partially driven by physiological arousal. Content that evokes high-arousal positive (awe) or negative (anger or anxiety) emotions is more viral. Content that evokes low-arousal, or deactivating, emotions (e.g., sadness) is less viral. These results hold even when the authors control for how surprising, interesting, or practically useful content is (all of which are positively linked to virality), as well as external drivers of attention (e.g., how prominently content was featured). Experimental results further demonstrate the causal impact of specific emotion on transmission and illustrate that it is driven by the level of activation induced. Taken together, these findings shed light on why people share content and how to design more effective viral marketing campaigns (Milkman, Jonah Berger and Katherine L., 2011). It is a content analysis of articles published in the New York Times. Role of users: No message can go viral unless the users decide. Therefore, the role of users in making content viral is paramount. The question is who are the ones that can share and create a trend that has the potential of making the post v i r a l ? Michael Trusov, Anand V. Bodapati and Randolph E. Bucklin’s 2010 paper titled ‘Determining Influential Users in Internet Social Networks’ identify the users of the internet who influence internet usage of other people, in turn potentially making something viral. The objective was to estimate the influence of each Social Networking site member on the site usage of other member on the basis of a simple metric of their activity level (Michael Trusov, Anand V. Bodapati and Randolph E. Bucklin , 2010). A user was considered ‘influential’ if his or her activity level, as captured by site log-ins over time, has a significant effect on others' activity levels and, consequently, on the site's overall page view volume. The authors propose a nonstandard form of Bayesian shrinkage implemented in a Poisson regression and apply the model to data obtained from a major Social Networking site, which wants to remain anonymous. ‘Seeding Viral Content: The Role of Message and Network Factors’ by Yuping Liu-Thompkins as a research, examines key aspects of the seeding strategy by tracking the diffusion of 101 new videos published on YouTube through a Content analysis of No. of seeds, their influence and homogeneity. The results of this study suggest that a positive outcome is more likely if more seeds are used to start a viral campaign. Results show that it is best to start a viral campaign with consumers who have a strong tie with the viral message originator. Analysis showed that it is not ideal to use seed consumers with a large number of connections. A moderately heterogeneous group of consumers can best increase the reach of a viral message to more diverse consumer populations ( L iu -Thompkins, 2012). Studies identified several key factors for why a video becomes viral. However, they did not address the path videos take to reach wild popularity. The next step will be examining the route a viral video takes on the web. Authors such as, Wallsten (2008) argue that much of the reason a video becomes popular can be attributed to its distribution through social networks. For this reason, continuing research on this topic should be combined with social media pathways. By understanding how and why a video becomes viral, and how social media promotes the medium, fabricating viral videos will become more of an art form than a guessing game. Rationale for this study The phenomena of viral videos of different nature are a recent development in the context of mass media research over the years. The researchers have been able to find different studies under variety of themes but not a body of work which could take any theme into greater depths.

The need for this study is also vital because Punjab would be going in for elections in the coming year and this will be the apt time to observe the phenomena of the online nature of political campaigns. Recent parliamentary elections in India (2014) have already demonstrated that social media and online campaigns have been used effectively. It is only obvious that they will be used predominantly in this election as well. This research will, therefore, observe the videos whose shares from the official pages made them viral. Theoretical Perspective In the early 40s, before the invention of television, Lazarsfeld, Berelson and Goudet conducted an American survey on mass campaigns and gave the multi step flow theory of communication. The study revealed that informal social relationships had played a part in modifying the manner in which individuals selected content from the media campaign. The study also indicated that ideas often flow from the radio and newspapers to opinion leaders and from them to the less active sections of society. Thus, informal social groups have some degree of influence on people and mould the way they select media content and act on it. According to this model, ideas flow from mass media - to opinion leader - to the majority of the population. The ‘viral’ phenomenon is all about the selecting and sharing of content by people once opinion leaders share it on mass media (here, internet) Diffusion of Innovation (DOI) Theory developed by E.M. Rogers in 1962, originated in communication to explain how, over time, an idea or product gains momentum and diffuses (or spreads) through a specific population or social system. It traces the process by which a new idea or practice is communicated through certain channels over time among members of a social s y s t e m . The model describes the factors that influence people's thoughts and actions and the process of adopting a new technology or idea. For anything to go ‘viral’, it has to be viewed and shared by people over a time period, which are the initial days. Once it gains momentum, it will be shared i.e. diffusion will take place. Thus, it is an essential model to be followed by creators of content aiming at virality. Uses and gratification theory is the theory which explains of how people use media for their need and gratification. As media users become increasingly confronted with choices, this approach should direct our attention to the audience. For this study, this theory’s relevance comes in terms of users of the internet who will watch videos only if it gives them gratification, only then will it be shared and will have the potential to go viral. This is an important theory for content creators to keep in mind as to how to make content which will fall into the categories of needs and gratifications of their prospects. Propounded by Elisabeth Noelle-Neumann, the spiral of silence theory states that the media publicizes opinions that are mainstream and people adjust their opinions according to their perceptions to avoid being isolated. Individuals who perceive their own opinion as being accepted will express it, whilst those who think themselves as being a minority, suppress their views. Innovators and change agents are unafraid to voice different opinions, as they do not fear isolation. The content created to go viral must directly or indirectly concur with the majority opinion or must make their opinions that of the majority especially in case of political campaigns. Formulated by Albert Bandura at Stanford University, the social learning theory specifies that mass-m e d i a messages give audience members an opportunity to identify with attractive characters that demonstrate behaviour, engage emotions, and allow mental rehearsal and modelling of new behaviour. The behaviour of models in the mass media also offers vicarious reinforcement to motivate audience members' adoption of the behaviour. The viral content creators will definitely want to employ these techniques for people to relate to their content and trigger sharing patterns that will make their post viral. The Agenda setting theory puts forth the ability of the media to influence the significance of events in the public's mind. The media set the agenda for the audience's discussion and mentally order and organize their world. McCombs and Shaw assert that the agenda-setting function of the media causes the correlation between the media and public ordering of priorities. The people most affected by the media agenda are those who have a high need for 12

Amity Journal of Media & Communication Studies (ISSN 2231 – 1033) Copyright 2016 by ASCO 2016, Vol. 6, No. 2 Amity University Rajasthan orientation. Content that aims to go viral will have to influence minds that the events referred to are of high significance and should be discussed by them. Developed by Ball-Rokeach and De F lu e r , the key idea behind the Media dependency theory is that audiences depend on media information to meet needs and reach goals, and social institutions and media systems interact with audiences to create needs, interests, and motives in the person. The degree of dependence is influenced by the number and centrality of information functions and social stability. New media is fast growing and more and more people are depending on it for information. Thus, In order for a message to go viral, it has to seem credible and public should become dependent on it enough to share it in large numbers.

Objectives • To identify th e popular political videos of Punjab’s political leaders • To analysis the content of the popular videos • To identify viral videos

Methodology This study uses multi -stage sampling process. In the first stage, the three top politicians belonging to three major parties are identified. The official Facebook pages of the selected political leaders are chosen as the universe of the study. In the time frame of the study i.e.1st January, 2016 to 1stJune 2016, the videos have been identified. The chosen videos are those that have more than 400 shares at the official pages of leaders from the 3 most important parties in Punjab: Deputy Chief Minister Sukhbir Singh Badal from SAD-BJP (Since the CM does not have an official page on Facebook), Former CM Amarinder Singh from Congress and AAP Member of Parliamnet Bhagwant Mann as he had declared himself as the CM candidate of the party on record in 2015.

In the third stage of the methodology, `view: share’ formula is applied to calculate the extent of virality of the videos.

The units of analysis are as below: • The genre of the video: whether it was a speech, a visit/rally, an interview, a video message, a song or something else. • The content of the video • Appeal(s) used • Emotional elements used • Topic/theme

Timeframe

This study focuses on videos from 1st January, 2016 to 1stJune 2016.

Data Presentation and Analysis

The videos shortlisted from the pages have been watched, analysed and elements form the content have been noted. The data is presented in tabular form with the leaders mentioned in alphabetical order.

Amarinder Singh (Congress) Date No of views Number of Views : Shares Content (in shares (Ratio) thousands) April 19 35 420 83:1 Personal video message on reaching America. Appeal to oneness of NRI’s Mar 16 24 413 58:1 Interview to channel; discusses current issue (SYL), demeans rival. Appeal to patriotism and is provocative 13

in nature. Feb 7 26 572 45:1 Personal video message, talks of development strategy, unemployment and drugs and youth in politics. Demeans rival and uses emotional appeal Feb 3 25 551 45:1 Speech at Panjab University. Talks about youth education and drugs followed by a QnA session. Mostly uses development appeal. Jan 28 51 442 115:1 Short video showing audience response on arrival in Panjab University. Jan 28 33 450 73:1 Personal video message explaining boycott of Khadoor Sahib by-election. Demeans rival.

Jan27 26 456 57:1 Press conference on election boycott announcement, talks of sacrilege and Bargari firing, demeans rival and is provocative in nature.

Jan 10 48 466 103:1 Personal message inviting people to maghi mela; uses religious appeal.

Jan 8 51 536 95:1 Interview with zee news; demeaning rival.

Table 1: Views: Shares ratio on Captain Amrinder Singh’s timeline on Facebook

Figure 3: FB page of Captain Amrinder Singh

Bhagwant mann (AAP) Date uploaded Number of views Number of Views : Shares Content (in thousands) shares (Ratio) May 17 72 821 88:1 Media coverage of the rally at Chandigarh. May 16 113 1555 73:1 Personal video message thanking people for being a part of the rally and being non- violent. May 15 50 400 125:1 Personal video message asking people to come for rally, stay non violent. May 15 113 1046 108:1 Personal video message asking

people to join him in gheraoing CM’s residence in Chandigarh. May 7 109 2050 53:1 ‘Global Punjab’ interview with Bhagwant Mann about Zee blackout; calls it a threat to media and promises breaking the cable mafia network when in power May 6 163 3473 47:1 Personal video criticising Zee network blackout on fast way cable network, blaming ruling party for the same and expressing solidarity towards the channel. May 5 90 470 191:1 Public video; Indians stuck in Saudi Arabia thanking Bhagwant Mann for helping them come back to India Apr 26 103 576 178:1 Public video; Indians stuck in Saudi Arabia thanking Bhagwant Mann for helping them come back to India Mar 23 198 1117 177:1 Personal message about going to khatkar kalaan, Bhagat Singh and then holla mahala rally cum program. Uses religious appeal.

Mar 7 92 2086 44:1 Public video, boys stranded in Saudi Arabia talking about their problems. Mar6 52 1561 33:1 Speech in parliament; demeans rival and criticizing working of Prime Minister Mar1 204 1331 153:1 Kejriwal’s car attacked in Punjab. Feb27 145 2075 70:1 Kejriwal’s NDTV interview; talks about Punjab problems- farmer suicides, loans, no compensation, drugs, cancer and demean rival. Feb26 87 921 94:1 Saudi Arabian boys video just before returning home, thanking Mann. Feb18 83 1106 75:1 Public kabadi cup video saying that we will vote for AAP; poem praising AAP and demeaning SAD. Feb11 203 2339 87:1 Saudi Arabian boys video just before returning home, thanking Mann. Feb11 212 3053 69:1 Personal message shot outside Videsh Mantralya, informing of help provided to Saudi Arabian boys. Feb11 153 3046 50:1 Public-made spoof film dubbed with Sukhbir Badal’s speech, showing Kirron Kher fed up. Feb11 58 1752 33:1 Public-made poem for Kejriwal and AAP and demeaning SAD and BJP for price-rise and drug menace. Feb10 150 1753 86:1 Interview saying I will help Saudi Arabian boys and demeans government. Feb4 110 919 120:1 Public-made video against congress. Feb1 40 967 41:1 Public-made video; kids shouting AAP slogans in streets. Jan20 305 2397 127:1 Public- made video; volunteers in rally sloganeering and praising AAP. Jan18 135 2992 45:1 ABP Sanjha news report showing anti government slogans at SAD rally; people thrown out,

Jan15 203 3592 57:1 Personal message thanking people for coming to maghi mela rally.

Jan14 158 1039 152:1 Speech video praising people for coming to the rally.

Jan14 395 4201 94:1 Kejriwal’s entry at a rally in Punjab. Jan13 58 457 127:1 Maghi mela rally preparation video by Mann and invitation/request for public to come. Jan13 117 2676 44:1 AAP Canadian volunteer video demeaning rivals and listing Punjab’s problems and invite to Maghi mela rally. Jan13 226 2510 90:1 Same video as above (uploaded twice) Jan11 84 1574 53:1 AAP Mansa volunteers demeaning rivals and listing Punjab’s problems, praising AAP and Kejriwal and inviting people to Maghi mela rally

Jan10 188 3169 59:1 AAP overseas volunteer video, Muktsar Maghi mela invitation song demeaning rivals and talking of Punjab’s problems. Jan9 226 3968 57:1 Maghi mela invite personal video, Mann says it is to save punjab from drugs, corruption, mafia, poverty, unemployment, Congress and Badals.

Table 2: Views: Shares ratio on Bhagwant Mann’s timeline on Facebook

Figure 4: Facebook page of Bhagwant Mann

The closest ratio (33:1) is that of a video uploaded on March 6; it is an assembly speech of Bhagwant Mann wherein he recites a poem called ‘Achhe din’, which is a sarcastic comment on the work done by the prime minister in almost one year of his being in the office. It uses sarcasm to highlight the unfulfilled promises made by the PM at the time of campaigning. It is a common observation that stories that go viral have sensational content. This video is an 16

Amity Journal of Media & Communication Studies (ISSN 2231 – 1033) Copyright 2016 by ASCO 2016, Vol. 6, No. 2 Amity University Rajasthan example of the same wherein satirical recitation has been used to convey a message. This video has all the ingredients of a sensational news story and hence is the most popular video of all. A screen capture of the same is shown below.

Figure 5: Screen capture of the most popular video

Sukhbir Singh Badal (SAD)

Date uploaded Number of Number of Views : Shares Content views (in shares (Ratio) thousands) May 14 74 1399 53:1 Advertisement about Chappar Chirhi memorial ‘Fateh Burj’ May 10 22 429 51:1 Clipping of Sukhbir Badal’s China visit May 1 50 1067 47:1 Advertisement about SGGS University in Fatehgarh Sahib Apr 30 34 659 52:1 Advertisement about Driving school in Muktsar Apr 29 89 926 96:1 Advertisement about Jung-e-azadi memorial Apr 23 167 2324 72:1 Advertisement about automated driving test parks. Apr 15 137 1859 74:1 Sukhbir Badal speech at Baisakhi rally at Talwandi sabo talking about development schemes Apr 13 94 697 135:1 Sukhbir Badal and Prakash Badal speeches at Baisakhi rally at Talwandi sabo Apr 10 100 520 192:1 Sukhbir Badal boasting about the awards bagged by state in assembly Apr 8 80 457 175:1 Sukhbir Badal boasting about sewa kendras in assembly Apr 7 80 470 170:1 Sukhbir Badal boasting about Punjab’s industrial growth in assembly Apr 5 78 612 127:1 Sukhbir Badal boasting about their development schmes in assembly Apr 4 84 800 105:1 Sukhbir Badal boasts about Industrial and farming growth in Punjab in assembly. Apr 2 97 511 190:1 Sukhbir Badal boasting about schemes for farmers and villages in Punjab in assembly Apr1 37 711 52:1 Development advertisement video about Rajpura 1400 MW thermal plant. Mar31 41 712 58:1 Assembly speech on development, electricity i.e. powers 17

surplus state, 4-6 lane roads and demeaning rival. Mar30 34 578 59:1 Assembly speech on per capita income of state rise in last 9 years, development and poverty reduction. Mar29 55 823 67:1 Rally speech on farmer’s electricity bill subsidy. Mar29 111 1831 60:1 Golden temple ad about entrance plaza construction. Mar28 67 808 83:1 Assembly speech explaining productive debt and GDP increase comparing with other states.

Mar27 46 718 64:1 Speech on debt and GDP increase, demeaning rival. Mar27 178 2464 72:1 Virasat e Khalsa ad video. Mar26 97 423 Assembly speech on financial health of Punjab comparing with opposition, talking about development and demeaning rival. Mar20 96 1490 64:1 Advertisement of Indian School of Business.

Mar19 99 1318 75:1 Assembly speech demeaning rivals and demanding answer from cong leader-comedy/insult video. Mar18 133 1236 107:1 Mohali hockey stadium ad.

Mar15 134 1652 81:1 Chhapar Chirhi ad. Mar14 179 1649 108:1 Flyovers of Punjab; construction ad Mar11 330 1612 204:1 Ropar bypass ad. Feb19 159 427 372:1 Old age pension doubled ad. Feb13 266 1435 185:1 Rally speech using religious appeal, self praising leadership, Sikh heritage preservation, religious constructions and development of Amritsar. Feb13 182 761 239:1 Rally speech on drugs claiming Punjab not responsible and comparing with other states. Uses patriotic appeal (community)

Feb10 175 489 358:1 Some function speech on investment friendly Punjab; comparison with other states.

Feb10 172 552 311:1 Function speech on good governance policies, development and jobs. Feb9 178 833 213:1 Function speech on Punjab’s growth, development, power surplus state, demeaning congress, road network, bridges, Mohali airport, urban and rural development, health, education, sports and welfare schemes.

Feb8 173 728 238:1 Function speech on financial health of state, debts, revenue, tax devolution from centre, reduced poverty, health and education using central statistics. Feb7 243 978 248:1 Function speech using provocative and patriotic appeal, demeaning rival. Talks of revenue increase, financial health of Punjab along with comparison with other states.

Table 3: Views: Shares ratio on Sukhbir Badal’s timeline on Facebook

Figure 6: Facebook Page of Sukhbir Badal

Discussion

The main finding of this study is that none of the videos qualify as ‘viral’ according to the formulated methodology. No video could even feature in the twenties as far as the views: shares ratio of 24:1 is concerned. From videos having 400 shares to 4,000 shares and videos with 20,000 views to videos having 2,00,000 views, these figures stand useless as far as going ‘viral’ is concerned. This shows that the perception of online campaigning being very big is after all, not correct. Especially in Punjab, whose assembly elections are around the corner, where campaigning has already begun and reached its peak one expects better results but it is not to be. As far as all videos being similar are concerned, it is not true. Some videos are public- made while some are high quality advertisements. Some videos are funny parody songs while some are TV interviews. Some were hot burning issues while some were controversial and sensational. This goes to show that content and genres were contrasting and aplenty but none could create enough impact to trigger viewers to share them enough so as to go viral. Another thing to be kept in mind here is that many of the videos have content that demeans rival parties and politicians, or talk about development in the state while rampantly using the patriotic and religious appeals. This perhaps, as the results suggest, is not the way to go for Punjab’s politicians if they want to go ‘viral’ and help their own campaign in a state that has 70% of its population under the age of 40. In the journal article, ‘Going Viral – The Dynamics of Attention’of 2009by Bob Boynton (Boynton, 2009), the researcher analysed the content and statistics related to all the campaign videos of presidential candidates and results showed that no video of the 2008 US presidential election campaign went viral. Although, the methodology adopted was different, the results were the same as this study. The ‘viral’ phenomenon is all about the selecting and sharing of content by people once opinion leaders share it on the internet. With respect to the multi step theory of mass media, ideas often flow from the radio and newspapers to opinion leaders and from them to the less active sections of society. The online media however paints an absolutely new picture because the information flow on online medium is characterised by the `all-at-once-ness’ of information flow where the opinion leaders may be present at various levels and not necessarily amongst the media persons. In this context it is apparent that the multi step flow theory will have to be observed in a different manner on online media. The virality of videos depends upon the interest levels amongst the persons who view the videos online or with whom the videos may have been shared by another individual. The chances of the commonality of choices is very limited hence the videos need to have unique characteristics that may be found interesting by majority. In the present study only one

Amity Journal of Media & Communication Studies (ISSN 2231 – 1033) Copyright 2016 by ASCO 2016, Vol. 6, No. 2 Amity University Rajasthan video ( Mr. Bhagwant Mann’s speech) comes closest to being called `viral’ in a tentative way as discussed on page number 14-15. This video involves special combination of characteristics such as: 1.Celebrity 2. Theatrics 3. Poetry 4. Narration 5. Dramatic effect 6. Satire in content 7. Anti establishment 8. Prominent location (Parliament) 9. Credibility due to location and identity of individual 10. Human interest

The fact that presence of all these qualities could not make the video go viral in the `real’ sense of the word goes to prove that many more special qualities are required to make the video appeal to all sections of the masses because the opinion leaders may be present in any strata amongst the audiences. With respect to the uses and gratification theory,public is increasingly becoming selective due to the information overload online today. For someone to share a video, more that one of his needs have to be satisfied. It is becoming increasingly difficult to make people watch a video, sharing is an altogether different issue. Politicians have to keep in mind these things and prepare content which will make the public choose to watch their video. The reason for this should be that the video fulfils all their needs. The video should be such that the people are happy to emulate the sam behaviour to their advantage as social learning theory suggests. If he video is in consonance with the thought and behaviour of the target audinece they will be motivated to share the particular video. Thus, this element of motivation is an important feature that video makers must include to make potentially viral videos.This element is lacking in the studied videos and could be a major reason for the videos not being shared enough.If the media are able to keep a finger on the audience’s pulse they will be able to set the agenda for change. The videos are primarily created to initiate public discussion.The media (here news oriented media) set an agenda and make an issue popular. This quality is used in many videos but still those videos are not viral. The reason is that the set agendas are discussed but lack qualities of progressive mindsets discussed above. These agendas are used to blame the rivals which defeats the purpose. As the review of literature has pointed out positive, progress oriented, optimistic videos have a better chance of going viral, which does not seem to be the case in the above sample. In a study by Tyler West, ‘Going Viral: Factors That Lead Videos to Become Internet Phenomena’ (2011) 20 viral videos as listed by Times magazine are monitored to bring out the common elements which are responsible for a youtube video going viral. This study was trying to adopt the same approach but the finding that revealed that no video could qualify as viral changed the focus on suggesting how to make videos viral and what were the reasons why the studied videos failed to go viral. A study in 2010, ‘A multi-stage model of word-of- mouth influence through viral marketing’ by Arnaud De Bruyn, Gary L. Lilien, a model is developed to help identify the role word-of- mouth plays during each stage of a viral marketing recipients; decision-making process, including the conditions that moderate such influence. This study also established that electronic word of mouth i.e. sharing of the videos by viewers is the way to go viral. This was the basis of identifying virality by calculating the views to shares ratio of each video which had to be enough to say that it is spreading like information travels in case of word-of-mouth. 20

Conclusion

The study began by analysing videos to identify virality and hence the reasons behind it. Previous studies indicated that the general way of tagging a video as ‘viral’ just because it got a huge number of hits was not correct. Any video shared by a celebrity or a popular person can get those numbers. Thus, going by the biological definition of ‘viral’, the shares made by general people in comparison to the views can make it viral. Hence, a ratio was used for views and shares, whose relationship in a video can identify ‘virality’.

Keeping in mind the literature connected to this study, factors that identify ‘virality’ have been established. No set definition of ‘virality’ is in place but many studies have given their own definitions and criteria. This study has also established criteria for the same and recognized no video as viral which is the main finding of this study. Similarly, this study established a mechanism that drives virality. It says that sharing of the video by influential users or celebrities does not make it viral as they have an already established fan base. Thus it is not the current video/post that is driving the views and shares. Sharing by regular users has to be in such huge numbers that the video can be considered as viral.

The results of this study also show that internet is not as effective a medium to reach the masses as far as the popular perception goes because having large number of ‘views’ or ‘likes’ does not translate into a simple gesture such as ‘share’ in order for a video /message to go viral. Therefore, to expect that ‘Like’ to translate into a vote is too farfetched. There is no doubt about the fact that internet as a medium has the potential of maximum reach in minimum amount of time and money but extracting such results is a whole different ball game.

Reference Anurag Tiruwa, R. Y. (2014). Going Viral: An Effective Strategy for Marketing. RESEARCH AND SUSTAINABLE BUSINESS (pp. 598-603). New Delhi: EXCEL INDIA PUBLISHERS. Arnaud De Bruyn, Gary L. Lilien. (2008). A multi-stage model of word-of-mouth influence through viral marketing. Intern. J. of Research in Marketing, 151-163. Bolls, P. E. (2011). Spreading the virus: Emotional tone of viral advertising and its effect on forwarding intentions and attitudes. Journal of Interactive Advertising, 1-11. Boynton, B. (2009). Going Viral – The Dynamics of Attention. The Journal of Information Technology and Politics, 11-38. Christian Schulze, Lisa Schöler, & Bernd Skiera. (2014). Not all fun and games: Viral marketing for Utilitarian Products. Journal of Marketing, 1-19. Golan, Lance Porter and Guy J. (2006). From subservient chickens to brawny men: A comparison of viral advertising to television advertising. Journal of Interactive Advertising, Vol 6 No 2 , 26-33. Jason Y.C. Ho, M. D. (2010). Viral marketing: Motivations to forward online content. Journal of Business Research, 1000– 1006. Jenkins, B. (2011). Consumer Sharing of Viral Video Advertisements: A Look into Message and Creative Strategy Typologies and Emotional Content. Taoyuan: Capstone. Liu-Thompkins, Y. (2012). Seeding Viral Content The Role of Message and Network Factors. Journal of advertising research, 59-72. Mauro Bampo, M. T. (2008). The Effects of the Social Structure of Digital Networks on Viral Marketing Performance. Information Systems Research, 273-290. Milkman, Jonah Berger and Katherine L. (2011). What Makes online Content Viral? Journal of Marketing Research, 1-14. Michael Trusov, Anand V. Bodapati and Randolph E. Bucklin . (2010). Determining Influential Users in Internet Social Networks. Journal of Marketing Research, 643-658.

Ralf van der Lans, Gerrit van Bruggen, Jehoshua Eliashberg and Berend Wierenga. (2010). A Viral Branching Model for Predicting the Spread of Electronic Word of Mouth. Marketing Science, 348-365. S.Shankland. (2009 йил wednesday-February). “The Twitter Effect: Possibilities and Limits. Retrieved 2016 йил 23-April from www.cnet.com: http://www.cnet.com/news/the-twitter-effect-possibilities-and-limits/

Wallsten, K. (2009). “Yes We Can”: How Online Viewership, Blog Discussion, Campaign Statements and Mainstream Media Coverage Produced a Viral Video Phenomenon. YouTube and the 2008 Election Cycle in the US, 39-62. West, T. (2011). Going Viral: Factors That Lead Videos to Become Internet Phenomena. The Elon Journal of Undergraduate Research in Communications, 76-84.